The term "Equalizer" is a generic term for a signal processing device that can demodulate or decode a signal while compensating for certain channel imperfections. The channel imperfections most usually corrected by an equalizer are unequal attenuation or phase in the channel at different frequencies covered by the signal. Echoes are a manifestation in radio propagation that can cause variations in attenuation and phase across a frequency band. When digital radio transmission is employed, echoes sometimes give rise to intersymbol interference (ISI), in which a received signal sample depends on more than one adjacent symbol, having been "mixed" together by delayed echoes or propagation paths with different delays.
One type of equalizer known in the prior art is the Finite Impulse Response (FIR), or Transversal equalizer. A FIR equalizer attempts to construct an inverse of the channel imperfections in order to correct the signal. The disadvantage with this type of equalizer becomes apparent when the equalizer attempts to replace signal frequency components that have been totally deleted by a notch in the channel. In this situation, the equalizer attempts to create infinite gain at that frequency which unduly emphasizes noise.
Another known type of equalizer is the Decision Feedback (DF) equalizer. The Decision Feedback equalizer subtracts a weighted version of the already-decoded symbols from the next signal sample to be decoded, intending thereby to cancel the echo of the just-decoded symbol. The disadvantage with this type of equalizer is that, in cellular radio propagation environments, a direct wave can fade temporarily leaving the echo as the main signal-bearing component. In this case, the echo should not be thrown away, as in the technique used in the Decision Feedback equalizer, but rather utilized.
When it can be identified that the main path has greater attenuation than a delayed echo path, it is possible to sample and store the signal in a memory as a sequence of samples, and then retrospectively process the signal in time-reversed sample sequence so that the echo is decoded and the weaker main path is suppressed. An adaptive change to the demodulation direction is disclosed in U.S. Pat. No. 5,335,250 and in U.S patent application Ser. No. 08/218,236, filed Mar. 28, 1994.
Also known in the prior art is the Viterbi equalizer. The Viterbi equalizer avoids the deficiencies of both the FIR and DF equalizers by not attempting to undo the channel distortions and by being insensitive to whether the shortest or delayed paths are dominant. Instead, the Viterbi equalizer uses a model of the channel or propagation paths that is applied to hypothesized symbol sequences to predict what should be received. The hypothesis that most closely matches the actually received signal is then retained. The Viterbi method can be regarded as looking ahead, wherein the current symbol is separately decided with all possible hypotheses for a limited number of future symbols. These multiple decisions are then gradually trimmed as equivalent decisions are made on the future symbols. In the prior art Viterbi equalizer, if the channel changes during a multi-symbol decoding sequence, the channel model must be updated accordingly. U.S. Pat. No. 5,164,961 discloses a Viterbi equalizer that has a separately updated channel model for each of the future hypothesized symbol combinations, wherein the choice of which channel model survives to be updated and used is made in connection with the equivalent decisions on the future symbols. U.S. Pat. No. 5,331,666 describes a version of the so-called "channel model per state" adaptive Viterbi equalizer that does not use an explicit channel model, but rather uses direct predictions of signal samples for different symbol hypotheses which are updated directly after the symbol hypotheses are trimmed in number, without going through the intermediate stage of a channel model.
The foregoing adaptive Viterbi equalizer requires an initial channel estimate. In the prior art, an initial channel estimate is formed with the help of known symbol groups included in the transmitted data. These symbol groups are called syncwords or equalizer training patterns. When the channel is not expected to change between training patterns, the initial estimate may be used without updating between training patterns. This can lead to a loss of performance as a trade-off against complexity, when the initial estimate is based only on a few known training symbols.
Another known equalizer is the so-called "Blind" equalizer. Blind equalizers are supposed to function without the benefit of an initial estimate based on known symbols. Many prior art blind equalizers have been conceived for decoding continuous data transmissions over telephone trunk lines, for example. However, in these systems it is of no consequence if the systems lose a few hundred or a thousand symbols while acquiring initial convergence.